Agentic search over NASA EO-KG yields a 47k-pair benchmark where neural scoring plus LLM reranking raises MRR by over 5x then an additional 28%.
AutoNumerics: An au- tonomous, PDE-agnostic multi-agent pipeline for scien- tific computing
3 Pith papers cite this work. Polarity classification is still indexing.
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A constrained LLM front-end for FEniCS multi-physics simulations dispatches to human-written templates and achieves 100% valid parses plus 90-100% geometry success on benchmarks while avoiding LLM-generated solver code.
AutoPDE maintains an explicit solver strategy through PDE analysis, numerical method selection, and adaptive tuning, achieving 54.5% pass rate on PDE Agent Bench, 14.2 points above the strongest baseline.
citing papers explorer
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Bringing Agentic Search to Earth Observation Data Discovery
Agentic search over NASA EO-KG yields a 47k-pair benchmark where neural scoring plus LLM reranking raises MRR by over 5x then an additional 28%.
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A Constrained Natural-Language Interface for Variational Multi-Physics Finite Element Simulations in FEniCS
A constrained LLM front-end for FEniCS multi-physics simulations dispatches to human-written templates and achieves 100% valid parses plus 90-100% geometry success on benchmarks while avoiding LLM-generated solver code.
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AutoPDE: Reliable Agentic PDE Solving via Explicitly Represented Solver Strategies
AutoPDE maintains an explicit solver strategy through PDE analysis, numerical method selection, and adaptive tuning, achieving 54.5% pass rate on PDE Agent Bench, 14.2 points above the strongest baseline.